Homogenization of Portuguese long-term temperature data series: Lisbon, Coimbra and Porto

Three long-term temperature data series measured in Portugal were studied to detect and correct non-climatic homogeneity breaks and are now available for future studies of climate variability. Series of monthly minimum (Tmin) and maximum (Tmax) temperatures measured in the three Portuguese meteorological stations of Lisbon (from 1856 to 2008), Coimbra (from 1865 to 2005) and Porto (from 1888 to 2001) were studied to detect and correct non-climatic homogeneity breaks. These series together with monthly series of average temperature (Taver) and temperature range (DTR) derived from them were tested in order to detect homogeneity breaks, using, firstly, metadata, secondly, a visual analysis and, thirdly, four widely used homogeneity tests: von Neumann ratio test, Buishand test, standard normal homogeneity test and Pettitt test. The homogeneity tests were used in absolute (using temperature series themselves) and relative (using sea-surface temperature anomalies series obtained from HadISST2 close to the Portuguese coast or already corrected temperature series as reference series) modes. We considered the Tmin, Tmax and DTR series as most informative for the detection of homogeneity breaks due to the fact that Tmin and Tmax could respond differently to changes in position of a thermometer or other changes in the instrument's environment; Taver series have been used, mainly, as control. The homogeneity tests show strong inhomogeneity of the original data series, which could have both internal climatic and non-climatic origins. Homogeneity breaks which have been identified by the last three mentioned homogeneity tests were compared with available metadata containing data, such as instrument changes, changes in station location and environment, observing procedures, etc. Significant homogeneity breaks (significance 95% or more) that coincide with known dates of instrumental changes have been corrected using standard procedures. It was also noted that some significant homogeneity breaks, which could not be connected to the known dates of any changes in the park of instruments or stations location and environment, could be caused by large volcanic eruptions. The corrected series were again tested for homogeneity: the corrected series were considered free of non-climatic breaks when the tests of most of monthly series showed no significant (significance 95% or more) homogeneity breaks that coincide with dates of known instrument changes. Corrected series are now available in the frame of ERA-CLIM FP7 project for future studies of climate variability.

European Leaf Physiognomic Approach ELPA

Physiognomic traits of plant leaves such as size, shape or margin are decisively affected by the prevailing environmental conditions of the plant habitat. On the other hand, if a relationship between environment and leaf physiognomy can be shown to exist, vegetation represents a proxy for environmental conditions. This study investigates the relationship between physiognomic traits of leaves from European hardwood vegetation and environmental parameters in order to create a calibration dataset based on high resolution grid cell data. The leaf data are obtained from synthetic chorologic floras, the environmental data comprise climatic and ecologic data. The high resolution of the data allows for a detailed analysis of the spatial dependencies between the investigated parameters. The comparison of environmental parameters and leaf physiognomic characters reveals a clear correlation between temperature related parameters (e.g. mean annual temperature or ground frost frequency) and the expression of leaf characters (e.g. the type of leaf margin or the base of the lamina). Precipitation related parameters (e.g. mean annual precipitation), however, show no correlation with the leaf physiognomic composition of the vegetation. On the basis of these results, transfer functions for several environmental parameters are calculated from the leaf physiognomic composition of the extant vegetation. In a next step, a cluster analysis is applied to the dataset in order to identify "leaf physiognomic communities". Several of these are distinguished, characterised and subsequently used for vegetation classification. Concerning the leaf physiognomic diversity there are precise differences between each of these "leaf physiognomic classes". There is a clear increase of leaf physiognomic diversity with increasing variability of the environmental parameters: Northern vegetation types are characterised by a more or less homogeneous leaf physiognomic composition whereas southern vegetation types like the Mediterranean vegetation show a considerable higher leaf physiognomic diversity. Finally, the transfer functions are used to estimate palaeo-environmental parameters of three fossil European leaf assemblages from Late Oligocene and Middle Miocene. The results are compared with results obtained from other palaeo-environmental reconstructing methods. The estimates based on a direct linear ordination seem to be the most realistic ones, as they are highly consistent with the Coexistence Approach.